553 citations · 1.4k across the 41 of their papers we have counts for
5 papers · 1 filter
Controversial stimuli: pitting neural networks against each other as models of human recognition
Tal Golan, Prashant C. Raju, Nikolaus Kriegeskorte
Distinct scientific theories can make similar predictions. To adjudicate between theories, we must design experiments for which the theories make distinct predictions. Here we cons…
Visualizing Representational Dynamics with Multidimensional Scaling Alignment
Baihan Lin, Marieke Mur, Tim Kietzmann +1
Representational similarity analysis (RSA) has been shown to be an effective framework to characterize brain-activity profiles and deep neural network activations as representation…
Deep Learning for Cognitive Neuroscience
Katherine R. Storrs, Nikolaus Kriegeskorte
Neural network models can now recognise images, understand text, translate languages, and play many human games at human or superhuman levels. These systems are highly abstracted,…
Recurrence is required to capture the representational dynamics of the human visual system
Tim C Kietzmann, Courtney J Spoerer, Lynn Sörensen +3
The human visual system is an intricate network of brain regions that enables us to recognize the world around us. Despite its abundant lateral and feedback connections, object pro…
Neural network models and deep learning - a primer for biologists
Nikolaus Kriegeskorte, Tal Golan
Originally inspired by neurobiology, deep neural network models have become a powerful tool of machine learning and artificial intelligence, where they are used to approximate func…